Sustainable Energy Technologies and Assessments最新文献

{"title":"Substrates for constructed wetland–microbial fuel cell systems: Progress, performance, and perspectives","authors":"Ye Yang,&nbsp;Chengyun Li,&nbsp;Minghui Yu,&nbsp;Yisong Xu,&nbsp;Yingying Dong,&nbsp;Meiling Liu,&nbsp;Bo Wang,&nbsp;Wendong Wang","doi":"10.1016/j.seta.2026.105461","DOIUrl":"10.1016/j.seta.2026.105461","url":null,"abstract":"<div><div>Constructed wetland-microbial fuel cell (CW-MFC) integrate wastewater treatment with energy recovery, relying on substrates to dictate pollutant removal, electricity generation, and system stability. Addressing the lack of systematic syntheses, this review utilizes bibliometric analysis and critical evaluation to elucidate substrate evolution, performance characteristics, and electricity generation mechanisms. As research shifts toward multi-objective pollutant removal, substrates have transitioned from conventional structural media into multifunctional units governing mass transfer, microbial development, and electrochemical processes. This review further examines how substrate physicochemical properties and spatial configurations influence pollutant transformation, microbial processes, and electron transfer within CW–MFC systems. However, significant variations in conductivity, adsorption capacity, biocompatibility, and long-term stability persist. Furthermore, transitioning from laboratory studies to full-scale application remains hindered by economic constraints, functional integration complexities, and the absence of comprehensive evaluation frameworks. To advance practical implementation, future research must prioritize synergistic substrate design, scalable engineering feasibility, and sustainability-oriented assessments.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"94 ","pages":"Article 105461"},"PeriodicalIF":7.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149161406","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A critical review of auto-cascade and cascade heat pumps with zeotropic mixtures for heating applications","authors":"Dimitra Gonidaki,&nbsp;Evangelos Bellos","doi":"10.1016/j.seta.2026.105448","DOIUrl":"10.1016/j.seta.2026.105448","url":null,"abstract":"<div><div>The increasing demand for sustainable heating in both residential and industrial sectors has created the need for efficient heat pump technologies capable of achieving large temperature lifts. In this context, auto-cascade and cascade heat pumps employing zeotropic mixtures have emerged as promising solutions. The benefit of these systems over the conventional heat pump cycle lies in the temperature glide of zeotropic mixtures, which leads to the improvement of heat transfer and the reduction of exergy destruction in heat exchangers, along with the phase separation in auto-cascade cycles, which changes the mixture composition in the evaporator and condenser, resulting in lower pressure ratios. This paper presents a critical review of 48 studies on auto-cascade and cascade heat pumps with zeotropic mixtures for heating applications. The reviewed studies were classified into three categories: separator-based auto-cascade cycles, ejector-enhanced auto-cascade cycles, and conventional cascade cycles with zeotropic mixtures. System configuration, operating conditions, mixture selection, thermodynamic performance and economic results were collected and discussed. The review shows that most studies so far focus on heat production below 100 °C, mainly involving separator- and ejector-based auto-cascade systems, whereas higher-temperature applications were identified for cascade cycles with zeotropic mixtures. Advanced configurations incorporating vapor injection, multiple separators and ejector devices consistently outperform the basic auto-cascade cycle. Ejector-enhanced systems frequently exhibit favorable COP values, while cascade systems with mixtures are predominantly investigated at higher temperature lifts; however, the heterogeneous operating conditions prevent a universal performance ranking. The findings of this review highlight the potential of auto-cascade and cascade heat pumps for sustainable heating and encourage further research towards higher-temperature applications and industrial process heating. Future work should focus on experimental validation, dynamic modelling with adaptive mixture composition control, comprehensive techno-economic assessment, and the integration of these technologies into polygeneration systems and Carnot battery applications.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"94 ","pages":"Article 105448"},"PeriodicalIF":7.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149161464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scalable regional joint wind power forecasting method supporting dynamic incorporation of new farms","authors":"Jingwen Liu,&nbsp;Yongning Zhao,&nbsp;Yao Ru,&nbsp;Xu Lin,&nbsp;Yanxu Chen","doi":"10.1016/j.seta.2026.105450","DOIUrl":"10.1016/j.seta.2026.105450","url":null,"abstract":"<div><div>As wind farm clusters expand, reliable forecasting for newly constructed wind farms becomes increasingly important. However, these farms typically have limited historical power data during early operation, while their incorporation alters the structure and data distribution of the existing cluster. This paper proposes a scalable joint wind power forecasting method with a teacher-student architecture for dynamic cluster expansion. A teacher model is trained on existing wind farms to learn spatial adjacency and temporal attention patterns, which are used to construct a Behavior Infrastructure Graph (BIG). When new wind farms are incorporated, the BIG is expanded based on wind power correlations and used to initialize the expanded teacher model. The teacher model is then adapted using limited data from the new farms. Finally, knowledge distillation trains a student model under the joint supervision of the expanded teacher outputs and observed power data from the new farms. This allows the student model to inherit the teacher’s forecasting capability while learning farm-specific information. Case studies involving 35 wind farms demonstrate that the proposed method effectively expands the forecasting model, improves forecasting accuracy over longer forecast horizons for newly constructed wind farms, and maintains stable forecasting performance for existing wind farms.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"94 ","pages":"Article 105450"},"PeriodicalIF":7.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149161468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A resource-constrained marginal-benefit batch maintenance framework for wind turbine fleets under degradation risk","authors":"Yi Guo,&nbsp;Rongxi Wang,&nbsp;Yufan Li,&nbsp;Jiangbo Li,&nbsp;Yuxin Li,&nbsp;Zhen Wang,&nbsp;Jianmin Gao","doi":"10.1016/j.seta.2026.105465","DOIUrl":"10.1016/j.seta.2026.105465","url":null,"abstract":"<div><div>Maintenance timing decisions for wind turbine fleets are crucial for ensuring operational safety and economic efficiency under limited maintenance resources. However, fleet-level maintenance scheduling remains challenging because multiple turbines may enter degradation-related maintenance windows concurrently, while degradation behaviors and economic consequences are heterogeneous. This paper proposes a dual-interval and marginal-benefit batch maintenance (DMBM) framework for wind turbine fleets under degradation risk and resource constraints. Firstly, a degradation-boundary-driven dual-interval formulation is developed to transform predicted degradation trajectories into decision-oriented maintenance intervals, where the degradation-constrained interval defines the latest admissible maintenance boundary and the executable interval determines the actual repair period. Secondly, a capability-risk-value decision model is constructed to quantify capability loss, degradation-induced risk, downtime loss, maintenance expenditure, fixed startup cost, and continued-operation revenue within a unified joint decision cost. Furthermore, fleet-level batch feasibility is modeled by considering interval overlap, time concurrency, cost sharing, and minimum crew requirements, while a marginal batching benefit mechanism is introduced to identify economically meaningful batches and avoid excessive aggregation. A SCADA-based case study demonstrates that DMBM can transform turbine-level maintenance preferences into executable fleet-level batch schemes and outperforms benchmark strategies in joint decision cost, batch organization, maintenance adequacy, resource demand, and time efficiency.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"94 ","pages":"Article 105465"},"PeriodicalIF":7.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149161469","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Scheduling and energy management in a renewable-energy-driven microgrid with mobile charging robots: A structure-aware reinforcement learning approach","authors":"Taiwei Shi,&nbsp;Yingjun Shen,&nbsp;Zhe Song,&nbsp;Andrew Kusiak","doi":"10.1016/j.seta.2026.105440","DOIUrl":"10.1016/j.seta.2026.105440","url":null,"abstract":"<div><div>With the widespread adoption of electric vehicles (EVs) and advances in robotics, renewable-energy-driven microgrids equipped with mobile charging robots (MCRs) are emerging as a promising charging paradigm. By decoupling EV charging demand from real-time microgrid energy balance, MCRs improve operational flexibility while enhancing renewable energy utilization. In such systems, operators must jointly optimize MCR task assignments and charging-dock power schedules, resulting in a sequential decision-making problem with a structurally coupled hybrid action space. Unlike conventional hybrid-action settings, the discrete and continuous decisions act on different entities and are coupled without one-to-one correspondence, increasing the difficulty of policy learning. To address this challenge, this paper proposes a Structure-Aware Hybrid Proximal Policy Optimization (SA-HPPO) algorithm. The proposed method incorporates feasibility masking, sequential conflict-free action generation, and dock-activity-aware gated continuous control to explicitly encode feasibility constraints and structural dependencies into policy learning. Experiments using real-world renewable generation, load, and electricity-price data show that SA-HPPO achieves higher average profit than the compared learning-based and greedy policies. Extensive additional experiments demonstrate its generalizability and robustness across the tested operating conditions.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"94 ","pages":"Article 105440"},"PeriodicalIF":7.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149161478","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Production-stage carbon intensity of wind-based PEM hydrogen under temporal renewable-grid matching: an illustrative NSW case study","authors":"Yang Chen,&nbsp;Wenshan Guo,&nbsp;Huiying Zhang,&nbsp;Duu-Jong Lee,&nbsp;Soon Woong Chang,&nbsp;Dinh Duc Nguyen,&nbsp;Shicheng Zhang,&nbsp;Gang Luo,&nbsp;Huu Hao Ngo","doi":"10.1016/j.seta.2026.105454","DOIUrl":"10.1016/j.seta.2026.105454","url":null,"abstract":"<div><div>Proton exchange membrane (PEM) electrolysis coupled with wind power is a promising pathway for low-carbon hydrogen production, but annual renewable-energy accounting can obscure temporal mismatches between renewable generation and electrolyser demand. This study develops a GREET-informed production-stage carbon-intensity framework and applies it to an illustrative New South Wales (NSW) case at a 0.56 MW PEM scale. A normalised hourly NSW wind profile was scaled to project level and evaluated under four accounting and operational scenarios to distinguish the effects of annual versus hourly electricity matching, temporal grid-emission accounting, and wind-constrained operation. Although annual potential wind generation was matched to annual PEM electricity demand, hourly matching showed that 25.96 % of the electricity required for continuous operation was supplied by the grid. The corresponding core carbon intensity increased from 0.072 kg CO₂-e kg⁻¹ H₂ under annual-energy accounting to 9.425 kg CO₂-e kg⁻¹ H₂ under hourly matching. Applying temporally resolved grid-emission factors further increased the core carbon intensity to 9.726 kg CO₂-e kg⁻¹H₂, with grid-related emissions 3.22 % higher than under annual-average accounting. Eliminating grid electricity reduced PEM utilisation to 44.85 %, highlighting a trade-off between grid avoidance and hydrogen production. The results demonstrate that renewable-hydrogen carbon accounting is strongly influenced by the temporal alignment of renewable supply, electrolyser demand, and grid-emission conditions.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"94 ","pages":"Article 105454"},"PeriodicalIF":7.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149161530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated siting methodology for wind–hydropower pumped storage: A multi-criteria sustainability approach","authors":"Isabel C. Gil-García,&nbsp;Ana Fernández-Guillamón,&nbsp;Guillermo Martínez-Lucas,&nbsp;Ángel Molina-García","doi":"10.1016/j.seta.2026.105468","DOIUrl":"10.1016/j.seta.2026.105468","url":null,"abstract":"<div><div>At the core of the transition to low-carbon energy systems lies the need for integrated planning tools capable of balancing multiple sustainability dimensions. This study presents the Wind Hydro-Pumped Optimization Model (WHOM), a spatial decision-support tool for optimally siting wind turbines to power reversible hydropower pumping systems. Using Multi-Criteria Decision-Making (MCDM) approaches, WHOM evaluates technical, environmental, social, and economic factors, including proximity to reservoirs, grid access, and wind potential. The goal is to maximize the renewable input for the pumped storage, reduce transmission losses, and guide sustainable land-use planning aligned with the Sustainable Development Goals (SDGs). The model is evaluated in Spain, where the proposed wind power plant generates 27,355 MWh annually. Of this, 11,370 MWh are produced during nighttime in the windiest months, demonstrating the operational synergy between wind energy and hydro storage. Additionally, the system avoids around 11,000 tonnes of CO₂ emissions per year, supporting the decarbonization of the energy sector. The framework offers a replicable, holistic approach to energy planning that integrates technical performance with territorial and environmental compatibility.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"94 ","pages":"Article 105468"},"PeriodicalIF":7.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149205048","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Weather research and forecasting model and weibull-based wind resource assessment for Techno-Economic evaluation of coastal sites in India","authors":"Mohan Narayan Gupta,&nbsp;Debashis Paul,&nbsp;Jaya Singh,&nbsp;Harendra Kumar Yadav,&nbsp;Jahar Sarkar,&nbsp;Arnab Sarkar","doi":"10.1016/j.seta.2026.105457","DOIUrl":"10.1016/j.seta.2026.105457","url":null,"abstract":"<div><div>Accurate characterization of coastal wind resources is essential for reliable wind energy planning and techno-economic decision-making. This study evaluates the wind resource potential of Dhanuskodi, Gopalpur, and Visakhapatnam using the Weather Research and Forecasting model. Model performance was assessed through seasonal and diurnal variability, statistical validation, spatial analysis, and Weibull distribution fitting. The simulations successfully reproduced the temporal and seasonal characteristics of wind speed. The scale and shape parameters showed good agreement with observations, with percentage errors below 7%<strong>,</strong> confirming the model’s capability to represent wind-speed frequency characteristics. The techno-economic assessment demonstrated substantial spatial variability in turbine performance and project economics. Dhanuskodi emerged as the most promising site<strong>,</strong> exhibiting capacity factors of 0.45–0.57 and Levelized cost of energy (LCOE) values of 0.0226–0.0285 USD/kWh. Sensitivity analysis identified capital cost and discount rate as the dominant LCOE drivers, while O&amp;M costs and turbine lifetime also influenced economic performance. The GE 1.7–100 showed consistent cost-effectiveness across the investigated locations. Accounting for practical system losses increased LCOE by approximately 19–20%<strong>,</strong> providing a more realistic cost estimate. The findings support SDG 7 (Affordable and Clean Energy) by facilitating sustainable and economically viable wind energy development.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"94 ","pages":"Article 105457"},"PeriodicalIF":7.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149205054","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An adaptive mutual information and physics-prior-constrained learning framework for lithium-ion battery state of health estimation using electrochemical impedance spectroscopy","authors":"Xuewen Li,&nbsp;Xiangguo Yang,&nbsp;Bosi Yi,&nbsp;Yanxi Qiu,&nbsp;Yifan Liu,&nbsp;Qijia Son","doi":"10.1016/j.seta.2026.105451","DOIUrl":"10.1016/j.seta.2026.105451","url":null,"abstract":"<div><div>State of health(SOH) estimation of lithium-ion batteries is critical for safe and efficient battery system operation. However, existing electrochemical impedance spectroscopy(EIS)-based methods still suffer from limited feature adaptability, insufficient temporal degradation representation, and weak physical consistency, which collectively restrict reliable estimation under varying aging conditions. To address these issues, this study proposes an adaptive mutual information and physics-prior-constrained neural network framework(AM-PCNN). Mutual information(MI) quantifies statistical dependence between high-dimensional EIS features and SOH, enabling adaptive selection of degradation-sensitive features, while a temporal residual attention network captures degradation evolution from sequential EIS measurements. Furthermore, three physics prior constraints, including monotonic SOH degradation, resistance surrogate consistency, and abnormal capacity recovery suppression, are introduced to improve physical consistency. A genetic algorithm(GA) jointly optimizes MI threshold, physics constraint parameters, and network hyperparameters, reducing dependence on empirical settings. Under three temperature conditions, AM-PCNN achieves average root mean square error(RMSE), mean absolute error(MAE), mean absolute percentage error(MAPE), and coefficient of determination(R²) values of 0.520 %, 0.451 %, 0.678 %, and 0.971. The resistance surrogate shows strong overall negative correlation with SOH, with a Spearman coefficient of −0.8234. Contribution analysis indicates that imaginary features dominate under higher-temperature aging, supporting accurate and physically consistent EIS-driven SOH estimation.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"94 ","pages":"Article 105451"},"PeriodicalIF":7.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149161404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Operational resilience screening of a geographically grounded semi-synthetic Moroccan green-hydrogen network using CRITIC–TOPSIS and grouped machine learning","authors":"Mohamed-Amine Babay,&nbsp;Mustapha Adar,&nbsp;Ahmed Chebak,&nbsp;Mustapha Mabrouki","doi":"10.1016/j.seta.2026.105478","DOIUrl":"10.1016/j.seta.2026.105478","url":null,"abstract":"<div><div>This study assesses operational resilience in a geographically grounded, semi-synthetic Moroccan green-hydrogen distribution network. Real site coordinates anchor a directed graph with 58 nodes and 136 links, while capacities, demands, and connections are assumed rather than calibrated to existing infrastructure. Maximum-flow node-removal impacts under seven operating scenarios are normalised between the 10th and 90th percentiles, weighted with CRITIC, and aggregated using TOPSIS. The reference network supplies 63.8 % of demand. Low production receives the largest information weight (0.3527), followed by storage constraint (0.1871) and high pipeline losses (0.1528). The ranking agrees closely with an excluded archived compound-stress vector (Spearman ρ = 0.989; Kendall τ = 0.957; 100 % top-seven overlap). Seven ranked removals eliminate feasible delivery by disconnecting surviving production from consumers, although 156.4 production-capacity units remain; random removal still supplies 32.6 % of demand on average. A grouped dataset comprises 2,800 observations from 100 perturbed network realisations. Extra Trees achieves R² = 0.704, MAE = 0.0227, and RMSE = 0.0369 on 20 unseen realisations. Scenario-subset, aggregation, loss, capacity, topology, feature-ablation, and threshold checks distinguish local stability from dependence on network architecture. These results support methodological consequence screening within the stated model family. Hydraulic verification, transient analysis, project calibration, and complete historical parameter provenance are required before engineering deployment.</div></div>","PeriodicalId":56019,"journal":{"name":"Sustainable Energy Technologies and Assessments","volume":"94 ","pages":"Article 105478"},"PeriodicalIF":7.4,"publicationDate":"2026-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149161465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}